| 100.00% | Adverbs in dialogue tags | Target: ≤10% dialogue tags with adverbs | |
| 85.74% | AI-ism adverb frequency | Target: <2% AI-ism adverbs (58 tracked) | | wordCount | 1052 | | totalAiIsmAdverbs | 3 | | found | | 0 | | | 1 | | | 2 | | adverb | "deliberately" | | count | 1 |
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| | highlights | | 0 | "completely" | | 1 | "slowly" | | 2 | "deliberately" |
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| 100.00% | AI-ism character names | Target: 0 AI-default names (17 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 100.00% | AI-ism location names | Target: 0 AI-default location names (33 tracked, −20% each) | | codexExemptions | (empty) | | found | (empty) | |
| 66.73% | AI-ism word frequency | Target: <2% AI-ism words (290 tracked) | | wordCount | 1052 | | totalAiIsms | 7 | | found | | | highlights | | 0 | "weight" | | 1 | "footsteps" | | 2 | "echoing" | | 3 | "flicker" | | 4 | "electric" |
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| 100.00% | Cliché density | Target: ≤1 cliche(s) per 800-word window | | totalCliches | 0 | | maxInWindow | 0 | | found | (empty) | | highlights | (empty) | |
| 100.00% | Emotion telling (show vs. tell) | Target: ≤3% sentences with emotion telling | | emotionTells | 0 | | narrationSentences | 87 | | matches | (empty) | |
| 100.00% | Filter word density | Target: ≤3% sentences with filter/hedge words | | filterCount | 1 | | hedgeCount | 0 | | narrationSentences | 87 | | filterMatches | | | hedgeMatches | (empty) | |
| 100.00% | Gibberish response detection | Target: ≤1% gibberish-like sentences (hard fail if a sentence exceeds 800 words) | | analyzedSentences | 87 | | gibberishSentences | 0 | | adjustedGibberishSentences | 0 | | longSentenceCount | 0 | | runOnParagraphCount | 0 | | giantParagraphCount | 0 | | wordSaladCount | 0 | | repetitionLoopCount | 0 | | controlTokenCount | 0 | | repeatedSegmentCount | 0 | | maxSentenceWordsSeen | 45 | | ratio | 0 | | matches | (empty) | |
| 100.00% | Markdown formatting overuse | Target: ≤5% words in markdown formatting | | markdownSpans | 5 | | markdownWords | 37 | | totalWords | 1044 | | ratio | 0.035 | | matches | | 0 | "The Raven's Nest" | | 1 | "discreet clientele, unusual transactions, owners who never quite lined up with the paperwork." | | 2 | "Camden Town Station – Closed for Essential Refurbishment." | | 3 | "Stay on the surface. Call it in. Let uniform handle the descent." | | 4 | "Don't." |
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| 100.00% | Missing dialogue indicators (quotation marks) | Target: ≤10% speech attributions without quotation marks | | totalAttributions | 0 | | unquotedAttributions | 0 | | matches | (empty) | |
| 100.00% | Name drop frequency | Target: ≤1.0 per-name mentions per 100 words | | totalMentions | 31 | | wordCount | 1044 | | uniqueNames | 18 | | maxNameDensity | 0.86 | | worstName | "Quinn" | | maxWindowNameDensity | 2 | | worstWindowName | "Quinn" | | discoveredNames | | Shaftesbury | 1 | | Avenue | 1 | | Harlow | 1 | | Quinn | 9 | | Morris | 2 | | Raven | 1 | | Camden | 2 | | Chalk | 1 | | Farm | 1 | | Road | 1 | | Town | 1 | | Station | 1 | | Closed | 1 | | Essential | 1 | | Northern | 1 | | Line | 1 | | Tube | 1 | | You | 4 |
| | persons | | 0 | "Harlow" | | 1 | "Quinn" | | 2 | "Morris" | | 3 | "Raven" | | 4 | "You" |
| | places | | 0 | "Shaftesbury" | | 1 | "Avenue" | | 2 | "Camden" | | 3 | "Chalk" | | 4 | "Farm" | | 5 | "Road" | | 6 | "Town" | | 7 | "Station" |
| | globalScore | 1 | | windowScore | 1 | |
| 100.00% | Narrator intent-glossing | Target: ≤2% narration sentences with intent-glossing patterns | | analyzedSentences | 60 | | glossingSentenceCount | 1 | | matches | | 0 | "looked like a man counting breaths" |
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| 100.00% | "Not X but Y" pattern overuse | Target: ≤1 "not X but Y" per 1000 words | | totalMatches | 0 | | per1kWords | 0 | | wordCount | 1044 | | matches | (empty) | |
| 100.00% | Overuse of "that" (subordinate clause padding) | Target: ≤2% sentences with "that" clauses | | thatCount | 0 | | totalSentences | 87 | | matches | (empty) | |
| 100.00% | Paragraph length variance | Target: CV ≥0.5 for paragraph word counts | | totalParagraphs | 27 | | mean | 38.67 | | std | 27.36 | | cv | 0.708 | | sampleLengths | | 0 | 64 | | 1 | 7 | | 2 | 68 | | 3 | 65 | | 4 | 14 | | 5 | 82 | | 6 | 59 | | 7 | 6 | | 8 | 65 | | 9 | 34 | | 10 | 55 | | 11 | 10 | | 12 | 12 | | 13 | 56 | | 14 | 13 | | 15 | 3 | | 16 | 81 | | 17 | 20 | | 18 | 26 | | 19 | 67 | | 20 | 87 | | 21 | 4 | | 22 | 29 | | 23 | 15 | | 24 | 52 | | 25 | 40 | | 26 | 10 |
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| 97.20% | Passive voice overuse | Target: ≤2% passive sentences | | passiveCount | 2 | | totalSentences | 87 | | matches | | 0 | "being followed" | | 1 | "been rigged" |
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| 100.00% | Past progressive (was/were + -ing) overuse | Target: ≤2% past progressive verbs | | pastProgressiveCount | 2 | | totalVerbs | 162 | | matches | | 0 | "were fading" | | 1 | "was operating" |
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| 0.00% | Em-dash & semicolon overuse | Target: ≤2% sentences with em-dashes/semicolons | | emDashCount | 10 | | semicolonCount | 0 | | flaggedSentences | 9 | | totalSentences | 87 | | ratio | 0.103 | | matches | | 0 | "The suspect—tall, dark coat, moving with the lopsided urgency of a man who knew he was being followed—had already cleared the junction." | | 1 | "She burst out the other end onto a wider street and there it was—a green neon sign bleeding light through the downpour, the words *The Raven's Nest* flickering against a brick façade covered in old maps and yellowing photographs." | | 2 | "His head turned a fraction, and for a half-second she caught his face in the green glow—pale, angular, eyes that didn't belong to any face on her current caseload." | | 3 | "A rusted iron sign hung crooked on the railings: *Camden Town Station – Closed for Essential Refurbishment.* But the suspect was already six, seven, eight steps down, his coat tails flaring behind him, the sound of his footsteps echoing against tile and stone." | | 4 | "The air changed three steps in—drier, older, carrying the mineral tang of disused tunnels." | | 5 | "A single string of bulbs had been rigged along the far wall, casting just enough light to show the shape of a corridor that shouldn't have been there—a gap in the platform's edge, a low archway, and beyond it a flicker that wasn't electric." | | 6 | "She could see the edges of it now—stalls draped in dark cloth, shapes moving between them, faces she didn't recognise." | | 7 | "Something glinted at his throat—a medallion, a saint's face, worn bright by years of touch." | | 8 | "Or she could step into the archway, into the light, into a world she had spent three years telling herself didn't exist—the world that had taken Morris, that had swallowed her answers, that waited for her in places like this." |
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| 94.00% | Purple prose (modifier overload) | Target: <4% adverbs, <2% -ly adverbs, no adj stacking | | wordCount | 1058 | | adjectiveStacks | 1 | | stackExamples | | 0 | "suspect—tall, dark coat," |
| | adverbCount | 29 | | adverbRatio | 0.027410207939508508 | | lyAdverbCount | 5 | | lyAdverbRatio | 0.004725897920604915 | |
| 100.00% | Repeated phrase echo | Target: ≤20% sentences with echoes (window: 2) | | totalSentences | 87 | | echoCount | 0 | | echoWords | (empty) | |
| 100.00% | Sentence length variance | Target: CV ≥0.4 for sentence word counts | | totalSentences | 87 | | mean | 12 | | std | 9.85 | | cv | 0.821 | | sampleLengths | | 0 | 24 | | 1 | 18 | | 2 | 22 | | 3 | 7 | | 4 | 23 | | 5 | 11 | | 6 | 10 | | 7 | 17 | | 8 | 7 | | 9 | 16 | | 10 | 16 | | 11 | 12 | | 12 | 21 | | 13 | 3 | | 14 | 11 | | 15 | 39 | | 16 | 12 | | 17 | 2 | | 18 | 29 | | 19 | 5 | | 20 | 2 | | 21 | 29 | | 22 | 23 | | 23 | 3 | | 24 | 3 | | 25 | 25 | | 26 | 13 | | 27 | 17 | | 28 | 10 | | 29 | 7 | | 30 | 3 | | 31 | 17 | | 32 | 3 | | 33 | 4 | | 34 | 12 | | 35 | 43 | | 36 | 4 | | 37 | 6 | | 38 | 4 | | 39 | 3 | | 40 | 5 | | 41 | 10 | | 42 | 6 | | 43 | 7 | | 44 | 23 | | 45 | 4 | | 46 | 4 | | 47 | 2 | | 48 | 5 | | 49 | 8 |
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| 36.78% | Sentence opener variety | Target: ≥60% unique sentence openers | | consecutiveRepeats | 13 | | diversityRatio | 0.3103448275862069 | | totalSentences | 87 | | uniqueOpeners | 27 | |
| 83.33% | Adverb-first sentence starts | Target: ≥3% sentences starting with an adverb | | adverbCount | 2 | | totalSentences | 80 | | matches | | 0 | "Too fast for a man" | | 1 | "Then he moved again, faster," |
| | ratio | 0.025 | |
| 60.00% | Pronoun-first sentence starts | Target: ≤30% sentences starting with a pronoun | | pronounCount | 32 | | totalSentences | 80 | | matches | | 0 | "She pushed off the wall" | | 1 | "Her shoes hit the slick" | | 2 | "She didn't allow herself to" | | 3 | "She didn't allow herself the" | | 4 | "It sat where it always" | | 5 | "He was fast." | | 6 | "She burst out the other" | | 7 | "His head turned a fraction," | | 8 | "Her radio crackled." | | 9 | "She ignored it." | | 10 | "She didn't vault." | | 11 | "She climbed, one foot finding" | | 12 | "Her ankle screamed." | | 13 | "She ignored that too." | | 14 | "She drew her weapon." | | 15 | "She knew what the procedure" | | 16 | "She'd written enough of those" | | 17 | "You don't pursue a fleeing" | | 18 | "You call for backup." | | 19 | "You establish a perimeter." |
| | ratio | 0.4 | |
| 28.75% | Subject-first sentence starts | Target: ≤72% sentences starting with a subject | | subjectCount | 69 | | totalSentences | 80 | | matches | | 0 | "The rain came down in" | | 1 | "Detective Harlow Quinn ducked under" | | 2 | "The suspect—tall, dark coat, moving" | | 3 | "She pushed off the wall" | | 4 | "Her shoes hit the slick" | | 5 | "The leather watch on her" | | 6 | "She didn't allow herself to" | | 7 | "She didn't allow herself the" | | 8 | "The suspect cut left down" | | 9 | "Quinn followed, one hand dropping" | | 10 | "It sat where it always" | | 11 | "The alley stank of rotting" | | 12 | "He was fast." | | 13 | "She burst out the other" | | 14 | "Quinn had walked past this" | | 15 | "The reports on it were" | | 16 | "The suspect didn't go in." | | 17 | "His head turned a fraction," | | 18 | "Her radio crackled." | | 19 | "She ignored it." |
| | ratio | 0.863 | |
| 0.00% | Subordinate conjunction sentence starts | Target: ≥2% sentences starting with a subordinating conjunction | | subConjCount | 0 | | totalSentences | 80 | | matches | (empty) | | ratio | 0 | |
| 9.97% | Technical jargon density | Target: ≤6% sentences with technical-jargon patterns | | analyzedSentences | 43 | | technicalSentenceCount | 8 | | matches | | 0 | "The rain came down in sheets, hammering the pavement of Shaftesbury Avenue with a force that turned the neon reflections into a smeared watercolour." | | 1 | "The suspect—tall, dark coat, moving with the lopsided urgency of a man who knew he was being followed—had already cleared the junction." | | 2 | "She burst out the other end onto a wider street and there it was—a green neon sign bleeding light through the downpour, the words *The Raven's Nest* flickering …" | | 3 | "His head turned a fraction, and for a half-second she caught his face in the green glow—pale, angular, eyes that didn't belong to any face on her current caselo…" | | 4 | "A rusted iron sign hung crooked on the railings: *Camden Town Station – Closed for Essential Refurbishment.* But the suspect was already six, seven, eight steps…" | | 5 | "A single string of bulbs had been rigged along the far wall, casting just enough light to show the shape of a corridor that shouldn't have been there—a gap in t…" | | 6 | "The suspect had stopped at one of the stalls, leaning over a counter, his hand outstretched toward something that glowed faintly amber." | | 7 | "A man, young, olive-skinned, dark curly hair plastered to his forehead by the rain that had found its way down here somehow." |
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| 100.00% | Useless dialogue additions | Target: ≤5% dialogue tags with trailing filler fragments | | totalTags | 0 | | uselessAdditionCount | 0 | | matches | (empty) | |
| 100.00% | Dialogue tag variety (said vs. fancy) | Target: ≤10% fancy dialogue tags | |